An Algorithm for Sensor Data Uncertainty Quantification

  title={An Algorithm for Sensor Data Uncertainty Quantification},
  author={James Timothy Meech and Phillip Stanley-Marbell},
  journal={IEEE Sensors Letters},
This letter presents an algorithm for reducing measurement uncertainty of one physical quantity when oversampling measurements of two physical quantities with correlated noise. The algorithm assumes that the aleatoric measurement uncertainty in both physical quantities follows a Gaussian distribution and relies on sampling faster than it is possible for the measurand (the true value of the physical quantity that we are trying to measure) to change (due to the system thermal time constant) to… 
1 Citations

Figures from this paper



A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

Both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters are reviewed.

Efficient Programmable Random Variate Generation Accelerator From Sensor Noise

A method for non-uniform random number generation based on sampling a physical process in a controlled environment that reduces the error of Monte Carlo integration of a univariate Gaussian by 1068 times while doubling the speed of the Monte Carlo simulation.

Collaborative Multi-Sensing in Energy Harvesting Wireless Sensor Networks

  • Vini GuptaS. De
  • Computer Science
    IEEE Transactions on Signal and Information Processing over Networks
  • 2020
This article presents an adaptive multi-sensing (MS) framework for a network of densely deployed solar energy harvesting wireless nodes. Each node is mounted with heterogeneous sensors to sense

An Experimental Thermal Time-Constant Correlation for Hydraulic Accumulators

A thermal time-constant correlation based on experimental data is presented for gascharged hydraulic accumulators. This correlation, along with the thermal timeconstant model, permits accurate

A New Approach to Linear Filtering and Prediction Problems

The clssical filleting and prediclion problem is re-examined using the Bode-Shannon representation of random processes and the ?stat-tran-sition? method of analysis of dynamic systems. New result

Progress in the development of semiconducting metal oxide gas sensors: a review

Since the first suggestion, during the 1950s, that high-surface-area metal oxides could be used as conductometric gas sensors enormous efforts have been made to enhance both the selectivity and the

Fast, flexible, cycle-accurate energy estimation

  • Phillip Stanley-MarbellM. Hsiao
  • Computer Science
    ISLPED'01: Proceedings of the 2001 International Symposium on Low Power Electronics and Design (IEEE Cat. No.01TH8581)
  • 2001
A fast, flexible, cycle-accurate architectural simulator, Myrmigki, that models a commercial microcontroller and microprocessor family, and enables cycle- Accurate power dissipation analyses through a combination of instruction level power analysis and circuit activity estimation.

Warp: A Hardware Platform for Efficient Multimodal Sensing With Adaptive Approximation

Warp is presented, the first open hardware platform designed explicitly to support research in approximate computing, in a 3.6 cm × 3.3 cm × 0.5 cm device, which supports a wide range of precision and accuracy versus power and performance tradeoffs.

Frequency‐domain description of a lock‐in amplifier

The basic principles behind the operation of a lock‐in amplifier are described. Particular emphasis is placed on looking at the frequency components of the signal present at the various stages of the

Near-sensor and In-sensor Computing